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Twitter Critical Phases Identification Based on Time Series of Microposts Analysis

Ch. 2795. P. 140–145.
Dmitriev A., Dmitriev V., Balybin S.

Based on the basic principles of the self-organized criticality theory, we proposed an identifiers of network criticality. The identifiers allow you to determine the subcritical and supercritical phases of Twitter, using only the results of the analysis of the time series of microposts. The most significant result is the existence of two classes of time series of microposts and tweet Ids corresponding to them. The first class of the time series corresponds to the subcritical phase of the network. On the contrary, the second class corresponds to the supercritical phase.

Language: English
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Keywords: self-organized criticalitydetrended fluctuation analysisTwitter time seriesсамоорганизованная критичностьSubcritical PhaseSupercritical PhaseDFAсубкритическая фазасуперкритическая фазавременные ряды Twitter

In book

Proceedings of the Conference on Modeling and Analysis of Complex Systems and Processes 2020 (MACSPro 2020)
Vol. 2795. , CEUR Workshop Proceedings, 2020.
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